A novel approach for resilient modulus prediction using extreme learning machine-equilibrium optimiser techniques-Reference-Cited by-同舟云学术

A novel approach for resilient modulus prediction using extreme learning machine-equilibrium optimiser techniques

Published:2021-03-15 Issue: Volume: Page:1-11
ISSN:1029-8436
Container-title:International Journal of Pavement Engineering
language:en
Short-container-title:International Journal of Pavement Engineering

Author:

Gabr Alaa R.¹,Roy Bishwajit²,Kaloop Mosbeh R.¹³⁴^ORCID,Kumar Deepak⁵,Arisha Ali¹,Shiha Mohamed¹,Shwally Sayed¹,Hu Jong Wan³⁴,El-Badawy Sherif M.¹^ORCID

Affiliation:

1. Public Works and Civil Engineering Department, Mansoura University, Mansoura, Egypt

2. Department of Civil Engineering, National Institute of Technology Patna, Patna, India

3. Department of Civil and Environmental Engineering, Incheon National University, Incheon, Korea

4. Incheon Disaster Prevention Research Center, Incheon National University, Incheon, Korea

5. Department of Computer Science and Engineering, National Institute of Technology Patna, Patna, India

Funder

Korea Agency for Infrastructure Technology Advancement

the Ministry of Land, Infrastructure and Transport

Publisher

Informa UK Limited

Subject

Mechanics of Materials,Civil and Structural Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/10298436.2021.1892109

Reference53 articles.

1. AASHTO, 1993. AASHTO guide for design of pavement structures. In: Sustainable waste management and recycling: construction demolition waste: proceedings of the international conference organised by the concrete and masonry research group.

2. Evaluation of Resilient Modulus of Subgrade and Base Materials in Indiana and Its Implementation in MEPDG

3. Application of ANN in Pavement Engineering: State-of-Art

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